For example, the semantic categorical prior is used to generate richer and more realistic textures with the help of spatial feature transform (SFT) in SFTGAN[1]}. With this information from high-level tasks, similar LR patches can be easily distinguished and more natural textual details can be generated. In SPSR [2]}, the authors utilized the gradient maps to guide image recovery to solve the problem of structural distortions in the GAN-based methods. Among them, the gradient maps are obtained from a gradient branch and integrated into the SR branch to provide structure prior. With the help of gradient maps, we know which region should be paid more attention to, so as to guide the image generation and reduce geometric distortions.
